Special issue on tech mining

Cunningham, Scott; Porter, Alan L.; Newman, Nils C.

doi:10.1016/j.techfore.2006.06.004

Cited by 24 publications

(6 citation statements)

References 13 publications

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“…It is remarkable to state that the data used in this paper cover granted patents. Database compilations of publications and patents are rarely timely, which creates indicators that permanently lag the discoveries (Cunningham et al , 2006). Therefore, when the latency between the application and grant approval is considered, this change can be attributed to a change in late 2010.…”

Section: Resultsmentioning

confidence: 99%

Updating technology forecasting models using statistical control charts

Durmuşoğlu

2017

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Purpose The purpose of this paper is to develop an approach that can detect abnormal deviations in the time series models for technology forecasting. The detected modifications provide a basis for understanding the determinants and impact of the corresponding change. Design/methodology/approach The proposed approach is based on monitoring residual values (the difference between the observation and the forecasted value) continuously using statistical control charts (SCCs). The residuals that are out of the expected limits are considered an alert indicating a remarkable change. To demonstrate the use of the proposed approach, a time series model was fitted to a number of TV-related patent counts. Subsequently, model residuals were used to determine the limits of the SCCs. Findings A number of patents granted in the year 2012 violated the upper control limit. A further analysis has shown that there is a linkage between the abnormal patent counts and the emergence of LCD TVs. Practical implications Change in technology may dramatically affect the accuracy of a forecasting model. The need for a parameter update indicates a significant change (emergence or death of a technology) in the technological environment. This may lead to the revision of managerial actions in R&D plans and investment decisions. Originality/value The proposed methodology brings a novel approach for abnormal data detection and provides a basis for understanding the determinants and impact of the corresponding change.

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Section: Resultsmentioning

confidence: 99%

Updating technology forecasting models using statistical control charts

Durmuşoğlu

2017

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“…Similarly, to study how the academic and industrial sector interact to create innovative methodologies and technologies, future research could use patent data, e.g. using tech mining (Cunningham, Porter, and Newman 2006) and trade journals/magazines databases, e.g. through the EBSCO's Business Source Complete database (see, e.g.…”

Section: Methodological Considerations For Bibliometric Studies In Msmentioning

confidence: 99%

Trends and topics in IJPR from 1961 to 2017: a statistical history

Romero-Silva

Marsillac

2018

International Journal of Production Research

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This paper studies the history of the International Journal of Production Research (IJPR) by analysing the topics that have received the most attention in each of the journal's publication years. Text mining exposed for scrutiny the most frequently mentioned and cited terms contained in the titles, abstracts and keywords of IJPR papers. Analyses suggest that the triad of scheduling/optimisation/simulation and supply-chain-related topics have been IJPR's mainstays, but valuable opportunities remain for relevant topics that have not yet been concurrently and frequently studied. Results also show that terms related to sustainability and risk management topics have gained recent relevance. In addition, IJPR appears to complement its modelling technique focus with empirical methodological approaches to provide a well-balanced perspective, since the 'case study' term is common. Finally, a linear relationship is found between the number of papers that have covered certain topics and the number of citations those topics have received, highlighting which topics had fewer or more citations than expected, given the number of papers that covered those topics. IJPR stands as one of the most prestigious and established journals in its field and the results from this study indicate the evolving interests of the field for over half a century.

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“…Most of the methods used are based on intelligent semantic technologies for searching, extracting and analyzing heterogeneous data from electronic information sources in line with the Big Data concept [12,13]. In particular, the Tech Mining methodology is proposed and applied in practice as a form of statistical contextual analysis of text documents based on scientific and technical resources (primarily scientific publications and patent databases) to identify breakthrough research and development and to characterize their innovative potential [14]. The Tech Mining technique is based on an approach called Text Mining, which is used to algorithmically identify and detect correlations, relationships, and previously unknown practically useful interpreted knowledge in text data fragments [15][16][17], which can be used to make decisions in various fields.…”

Section: Energy Technology Forecastingmentioning

confidence: 99%

Technology of Application of Software Tools for Energy Technology Forecasting

Kopaygorodsky¹

2019

Proceedings of the 21st International Workshop on Computer Science and Information Technologies (CSIT 2019)

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In this paper an approach to the collection and analysis of information for the task of scientific and technological forecasting is considered. The approach is based on the use of ontologies, Tech Mining and Data Analysis methods. The developed approach is supported by the distributed intellectual information system created by the author. The technology of using tools for solving the problem is presented.

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Special issue on tech mining

Cited by 24 publications

References 13 publications

Updating technology forecasting models using statistical control charts

Updating technology forecasting models using statistical control charts

Trends and topics in IJPR from 1961 to 2017: a statistical history

Technology of Application of Software Tools for Energy Technology Forecasting

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